Research Article
Performance Comparison for Mining Large Data from the Internet and Learning using ID3 Algorithm in a Docker versus Virtual Machine Environment
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 153 - Issue 7 |
| Published: Nov 2016 |
| Authors: Abishek Ravichandran, Aishwarya Sundararajan, V. Balasubramanian |
10.5120/ijca2016912100
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Abishek Ravichandran, Aishwarya Sundararajan, V. Balasubramanian . Performance Comparison for Mining Large Data from the Internet and Learning using ID3 Algorithm in a Docker versus Virtual Machine Environment. International Journal of Computer Applications. 153, 7 (Nov 2016), 18-22. DOI=10.5120/ijca2016912100
@article{ 10.5120/ijca2016912100,
author = { Abishek Ravichandran,Aishwarya Sundararajan,V. Balasubramanian },
title = { Performance Comparison for Mining Large Data from the Internet and Learning using ID3 Algorithm in a Docker versus Virtual Machine Environment },
journal = { International Journal of Computer Applications },
year = { 2016 },
volume = { 153 },
number = { 7 },
pages = { 18-22 },
doi = { 10.5120/ijca2016912100 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2016
%A Abishek Ravichandran
%A Aishwarya Sundararajan
%A V. Balasubramanian
%T Performance Comparison for Mining Large Data from the Internet and Learning using ID3 Algorithm in a Docker versus Virtual Machine Environment%T
%J International Journal of Computer Applications
%V 153
%N 7
%P 18-22
%R 10.5120/ijca2016912100
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Every day, 2.5 quintillion bytes of data are generated. A sizeable portion of the data is available through the internet. The efficacy of the decisions being made revolves around the extent to which analysis is performed on the procured data. Containers provide Operating System Virtualization and Linux Containers present secure execution environments by independently executing processes.[1]This paper aims at proving that the performance of Docker Container in mining large data from the internet and learning using ID3 algorithm to generate a decision tree to predict useful results is much better than the performance in a Virtual Machine Environment.
References
- Major Hayden, “Securing Linux Containers”, GIAC (GCUX) Gold Certification, July 26, 2015.
- Samuel T. King, George W. Dunlap, Peter M. Chen, “Operating System Support for Virtual Machines,” Proceedings of the 2003 USENIX Technical Conference, 2003.
- Young, C.J., “Extended Architecture and Hypervisor Performance,” Proceedings IEEE Computer Society Conference, Boston, MA, September 1971.
- James Turnbull,2014,’The Docker Book’
- http://faculty.simpson.edu/lydia.sinapova/www/cmsc310/LN310_AIMA/L13-ML-ID3.pdf
- ID3Algorithm,https://en.wikipedia.org/wiki/ID3_algorithm
- https://www.cise.ufl.edu/~ddd/cap6635/Fall-97/Short-papers/2.htm
- Jeffrey Dean and Sanjay Ghemawat, “MapReduce: Simplified Data Processing on Large Clusters,” Google,Inc.,OSDI 2004.
- Carl Boettiger, An introduction to Docker for reproducible research, with examples from the R environment, (2015) ACM SIGOPS Operating Systems Review, Special Issue on Repeatability and Sharing of Experimental Artifacts. 49(1), pp.71-79.
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